Competitive intelligence (CI) is key to develop the corporate innovation strategy. Proper competitive intelligence provides detailed analysis of the market, current and future competitors allowing the firm to craft precise action plans to compete and to pivot as market structures evolve. While most CI studies provide generic market forecast and some company profiles, usually lack depth to identify competitor innovation strategies. A unique and powerful competitive intelligence tool that helps identify and forecast competitor moves is semantic analysis.
Semantic analysis identifies patterns among very large data sets. The intelligence this tool provides helps us understand technology megatrends, corporate innovation and investment strategies.
Our team, using semantic analysis, was able to complete an extremely detailed “competitor innovation strategy” based on public information. A database of press releases, press articles, journal articles and patent applications was created. The database was further analyzed to identify patterns that provide insight into the company innovation strategy.
Case Study | Competitor Innovation Strategy
Project Objective: develop competitive profile of a multinational company that produces petrochemical based products (polymers, fertilizers and melamine) to understand the company current position and future innovation strategies.
Patent activity reached a peak during the 05-09 time period, 250-350 patent applications were completed every year. During time period 2010-14 patent activity dramatically decreased to 150-200 year.
The company has 3 research centers distributed over Europe, the centers are in Finland, Sweden and Austria. Additionally we identified where the IP was being generated. This analysis provided insight, the facility in Sweden did barely generate any IP during the last few years and a small team at the Austrian facility had pick up significant momentum, suggesting a centralization of the research center with their product development teams located in central Europe.
Finally a technical semantic analysis was completed on their patents and technical papers to understand potential new products and strategic direction. The image below shows the core issues researched, visualizing key research topics and key words. The linkages between key words identify the frequency of usage.
With the support of a subject matter expert in chemistry, we are able to translate the patent’s technical discussion into business and products applications. This analysis showed a clear product strategy focused on reducing the weight of their traditional core products (polypropylene). The application of these innovations are (1) copolymers which give the products characteristics intermediate between polyethylene and polypropylene, this material are mostly used on medical, and automotive packaging, and (2) products for electrical insulation.
The innovation strategy is aligned with a business transitioning to focus on polymers, while deemphasizing innovation on fertilizers and melamine.
All this information was obtained from the public domain, and analyzed in a matter of days. While semantic analysis of large databases will require sophisticated software, comparable analysis of middle market companies can be completed with basic search tools and open source software. This approach can show innovation strategies of companies, as well as trends in research for an industry or an application.
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